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bart-large-lora

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@@ -1,12 +1,12 @@
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  ---
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  license: apache-2.0
 
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  tags:
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  - generated_from_trainer
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  metrics:
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  - accuracy
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  - precision
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  - recall
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- base_model: facebook/bart-base
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  model-index:
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  - name: bart-base-lora
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  results: []
@@ -17,23 +17,23 @@ should probably proofread and complete it, then remove this comment. -->
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  # bart-base-lora
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- This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.6655
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- - Accuracy: 0.7963
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- - Precision: 0.7841
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- - Recall: 0.7963
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- - Precision Macro: 0.5968
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- - Recall Macro: 0.6325
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- - Macro Fpr: 0.0186
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- - Weighted Fpr: 0.0179
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- - Weighted Specificity: 0.9749
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- - Macro Specificity: 0.9847
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- - Weighted Sensitivity: 0.7963
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- - Macro Sensitivity: 0.6325
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- - F1 Micro: 0.7963
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- - F1 Macro: 0.6074
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- - F1 Weighted: 0.7859
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  ## Model description
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@@ -66,26 +66,26 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | Precision Macro | Recall Macro | Macro Fpr | Weighted Fpr | Weighted Specificity | Macro Specificity | Weighted Sensitivity | Macro Sensitivity | F1 Micro | F1 Macro | F1 Weighted |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:---------------:|:------------:|:---------:|:------------:|:--------------------:|:-----------------:|:--------------------:|:-----------------:|:--------:|:--------:|:-----------:|
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- | No log | 1.0 | 160 | 1.2642 | 0.6313 | 0.5477 | 0.6313 | 0.3009 | 0.3127 | 0.0428 | 0.0400 | 0.9351 | 0.9711 | 0.6313 | 0.3127 | 0.6313 | 0.2941 | 0.5769 |
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- | No log | 2.0 | 321 | 0.8962 | 0.7119 | 0.6939 | 0.7119 | 0.3937 | 0.4525 | 0.0285 | 0.0281 | 0.9669 | 0.9786 | 0.7119 | 0.4525 | 0.7119 | 0.4107 | 0.6960 |
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- | No log | 3.0 | 482 | 0.8204 | 0.7196 | 0.6953 | 0.7196 | 0.3974 | 0.4468 | 0.0278 | 0.0271 | 0.9653 | 0.9790 | 0.7196 | 0.4468 | 0.7196 | 0.3998 | 0.6885 |
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- | 1.2731 | 4.0 | 643 | 0.7519 | 0.7436 | 0.7186 | 0.7436 | 0.4131 | 0.4673 | 0.0244 | 0.0240 | 0.9695 | 0.9809 | 0.7436 | 0.4673 | 0.7436 | 0.4272 | 0.7248 |
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- | 1.2731 | 5.0 | 803 | 0.7364 | 0.7475 | 0.7524 | 0.7475 | 0.6132 | 0.5050 | 0.0243 | 0.0236 | 0.9679 | 0.9810 | 0.7475 | 0.5050 | 0.7475 | 0.4905 | 0.7286 |
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- | 1.2731 | 6.0 | 964 | 0.7273 | 0.7514 | 0.7423 | 0.7514 | 0.5784 | 0.5258 | 0.0237 | 0.0231 | 0.9699 | 0.9814 | 0.7514 | 0.5258 | 0.7514 | 0.5150 | 0.7311 |
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- | 0.7243 | 7.0 | 1125 | 0.6993 | 0.7645 | 0.7478 | 0.7645 | 0.5498 | 0.5565 | 0.0222 | 0.0215 | 0.9721 | 0.9824 | 0.7645 | 0.5565 | 0.7645 | 0.5453 | 0.7538 |
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- | 0.7243 | 8.0 | 1286 | 0.6952 | 0.7769 | 0.7639 | 0.7769 | 0.5682 | 0.5888 | 0.0207 | 0.0201 | 0.9731 | 0.9833 | 0.7769 | 0.5888 | 0.7769 | 0.5700 | 0.7649 |
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- | 0.7243 | 9.0 | 1446 | 0.6759 | 0.7823 | 0.7708 | 0.7823 | 0.5764 | 0.5877 | 0.0201 | 0.0195 | 0.9739 | 0.9838 | 0.7823 | 0.5877 | 0.7823 | 0.5699 | 0.7697 |
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- | 0.6098 | 10.0 | 1607 | 0.6705 | 0.7847 | 0.7720 | 0.7847 | 0.5899 | 0.6176 | 0.0199 | 0.0192 | 0.9732 | 0.9839 | 0.7847 | 0.6176 | 0.7847 | 0.5935 | 0.7724 |
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- | 0.6098 | 11.0 | 1768 | 0.6794 | 0.7909 | 0.7737 | 0.7909 | 0.5882 | 0.6237 | 0.0193 | 0.0185 | 0.9736 | 0.9843 | 0.7909 | 0.6237 | 0.7909 | 0.5988 | 0.7773 |
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- | 0.6098 | 12.0 | 1929 | 0.6836 | 0.7909 | 0.7816 | 0.7909 | 0.5973 | 0.6285 | 0.0192 | 0.0185 | 0.9742 | 0.9843 | 0.7909 | 0.6285 | 0.7909 | 0.6034 | 0.7802 |
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- | 0.5239 | 13.0 | 2089 | 0.6508 | 0.7932 | 0.7783 | 0.7932 | 0.5965 | 0.6273 | 0.0189 | 0.0183 | 0.9738 | 0.9845 | 0.7932 | 0.6273 | 0.7932 | 0.6046 | 0.7821 |
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- | 0.5239 | 14.0 | 2250 | 0.6588 | 0.7963 | 0.7823 | 0.7963 | 0.5957 | 0.6290 | 0.0186 | 0.0179 | 0.9746 | 0.9847 | 0.7963 | 0.6290 | 0.7963 | 0.6055 | 0.7852 |
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- | 0.5239 | 14.93 | 2400 | 0.6655 | 0.7963 | 0.7841 | 0.7963 | 0.5968 | 0.6325 | 0.0186 | 0.0179 | 0.9749 | 0.9847 | 0.7963 | 0.6325 | 0.7963 | 0.6074 | 0.7859 |
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  ### Framework versions
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  - Transformers 4.35.2
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  - Pytorch 2.1.0+cu121
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- - Datasets 2.18.0
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  - Tokenizers 0.15.1
 
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  ---
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  license: apache-2.0
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+ base_model: facebook/bart-large
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  tags:
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  - generated_from_trainer
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  metrics:
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  - accuracy
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  - precision
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  - recall
 
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  model-index:
11
  - name: bart-base-lora
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  results: []
 
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  # bart-base-lora
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+ This model is a fine-tuned version of [facebook/bart-large](https://huggingface.co/facebook/bart-large) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.6884
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+ - Accuracy: 0.8172
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+ - Precision: 0.8132
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+ - Recall: 0.8172
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+ - Precision Macro: 0.7584
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+ - Recall Macro: 0.7412
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+ - Macro Fpr: 0.0164
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+ - Weighted Fpr: 0.0157
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+ - Weighted Specificity: 0.9755
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+ - Macro Specificity: 0.9862
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+ - Weighted Sensitivity: 0.8172
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+ - Macro Sensitivity: 0.7412
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+ - F1 Micro: 0.8172
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+ - F1 Macro: 0.7417
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+ - F1 Weighted: 0.8124
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | Precision Macro | Recall Macro | Macro Fpr | Weighted Fpr | Weighted Specificity | Macro Specificity | Weighted Sensitivity | Macro Sensitivity | F1 Micro | F1 Macro | F1 Weighted |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:---------------:|:------------:|:---------:|:------------:|:--------------------:|:-----------------:|:--------------------:|:-----------------:|:--------:|:--------:|:-----------:|
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+ | No log | 1.0 | 160 | 0.9525 | 0.7157 | 0.6788 | 0.7157 | 0.3875 | 0.4416 | 0.0285 | 0.0276 | 0.9642 | 0.9787 | 0.7157 | 0.4416 | 0.7157 | 0.3958 | 0.6835 |
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+ | No log | 2.0 | 321 | 0.7733 | 0.7413 | 0.7296 | 0.7413 | 0.4491 | 0.4687 | 0.0252 | 0.0243 | 0.9668 | 0.9805 | 0.7413 | 0.4687 | 0.7413 | 0.4337 | 0.7231 |
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+ | No log | 3.0 | 482 | 0.7105 | 0.7738 | 0.7631 | 0.7738 | 0.5565 | 0.5408 | 0.0212 | 0.0205 | 0.9725 | 0.9831 | 0.7738 | 0.5408 | 0.7738 | 0.5271 | 0.7611 |
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+ | 1.08 | 4.0 | 643 | 0.7539 | 0.7576 | 0.7584 | 0.7576 | 0.5791 | 0.5613 | 0.0234 | 0.0223 | 0.9681 | 0.9817 | 0.7576 | 0.5613 | 0.7576 | 0.5497 | 0.7438 |
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+ | 1.08 | 5.0 | 803 | 0.6978 | 0.7831 | 0.7900 | 0.7831 | 0.7410 | 0.6492 | 0.0203 | 0.0194 | 0.9710 | 0.9836 | 0.7831 | 0.6492 | 0.7831 | 0.6354 | 0.7703 |
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+ | 1.08 | 6.0 | 964 | 0.5920 | 0.8156 | 0.8053 | 0.8156 | 0.7051 | 0.6889 | 0.0166 | 0.0159 | 0.9746 | 0.9860 | 0.8156 | 0.6889 | 0.8156 | 0.6860 | 0.8088 |
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+ | 0.5581 | 7.0 | 1125 | 0.6231 | 0.8187 | 0.8178 | 0.8187 | 0.7627 | 0.7425 | 0.0162 | 0.0156 | 0.9766 | 0.9864 | 0.8187 | 0.7425 | 0.8187 | 0.7393 | 0.8147 |
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+ | 0.5581 | 8.0 | 1286 | 0.6291 | 0.8141 | 0.8134 | 0.8141 | 0.7636 | 0.7307 | 0.0167 | 0.0160 | 0.9758 | 0.9860 | 0.8141 | 0.7307 | 0.8141 | 0.7329 | 0.8089 |
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+ | 0.5581 | 9.0 | 1446 | 0.6226 | 0.8242 | 0.8212 | 0.8242 | 0.7666 | 0.7340 | 0.0158 | 0.0150 | 0.9760 | 0.9867 | 0.8242 | 0.7340 | 0.8242 | 0.7365 | 0.8191 |
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+ | 0.3924 | 10.0 | 1607 | 0.6728 | 0.8110 | 0.8123 | 0.8110 | 0.7418 | 0.7289 | 0.0170 | 0.0164 | 0.9762 | 0.9858 | 0.8110 | 0.7289 | 0.8110 | 0.7240 | 0.8048 |
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+ | 0.3924 | 11.0 | 1768 | 0.6805 | 0.8095 | 0.8123 | 0.8095 | 0.7390 | 0.7303 | 0.0173 | 0.0165 | 0.9752 | 0.9856 | 0.8095 | 0.7303 | 0.8095 | 0.7263 | 0.8026 |
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+ | 0.3924 | 12.0 | 1929 | 0.6710 | 0.8133 | 0.8137 | 0.8133 | 0.7396 | 0.7306 | 0.0168 | 0.0161 | 0.9759 | 0.9859 | 0.8133 | 0.7306 | 0.8133 | 0.7284 | 0.8090 |
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+ | 0.2929 | 13.0 | 2089 | 0.6740 | 0.8187 | 0.8170 | 0.8187 | 0.7644 | 0.7360 | 0.0162 | 0.0156 | 0.9761 | 0.9863 | 0.8187 | 0.7360 | 0.8187 | 0.7368 | 0.8151 |
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+ | 0.2929 | 14.0 | 2250 | 0.6823 | 0.8180 | 0.8159 | 0.8180 | 0.7657 | 0.7336 | 0.0164 | 0.0156 | 0.9753 | 0.9862 | 0.8180 | 0.7336 | 0.8180 | 0.7361 | 0.8137 |
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+ | 0.2929 | 14.93 | 2400 | 0.6884 | 0.8172 | 0.8132 | 0.8172 | 0.7584 | 0.7412 | 0.0164 | 0.0157 | 0.9755 | 0.9862 | 0.8172 | 0.7412 | 0.8172 | 0.7417 | 0.8124 |
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  ### Framework versions
87
 
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  - Transformers 4.35.2
89
  - Pytorch 2.1.0+cu121
90
+ - Datasets 2.19.0
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  - Tokenizers 0.15.1